SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Optimization of sequence queries in database systems
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
The Design and Implementation of a Sequence Database System
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
SRQL: Sorted Relational Query Language
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Stream Cube: An Architecture for Multi-Dimensional Analysis of Data Streams
Distributed and Parallel Databases
Warehousing and Analyzing Massive RFID Data Sets
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Flowcube: constructing RFID flowcubes for multi-dimensional analysis of commodity flows
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Unsupervised pattern mining from symbolic temporal data
ACM SIGKDD Explorations Newsletter - Special issue on data mining for health informatics
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Supporting ranking pattern-based aggregate queries in sequence data cubes
Proceedings of the 18th ACM conference on Information and knowledge management
S-OLAP: an OLAP system for analyzing sequence data
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
An overview of business intelligence technology
Communications of the ACM
E-Cube: multi-dimensional event sequence analysis using hierarchical pattern query sharing
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Multiversion spatio-temporal telemetric data warehouse
ADBIS'09 Proceedings of the 13th East European conference on Advances in Databases and Information Systems
Disease evolution visualization through historized versions of medical images
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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Nowadays business intelligence technologies allow to analyze mainly set oriented data, without considering order dependencies between data. Few approaches to analyzing data of sequential order have been proposed so far. Nonetheless, for storing and manipulating sequential data the approaches use either the relational data model or its extensions. We argue that in order to be able to fully support the analysis of sequential data, a dedicated new data model is needed. In this paper, we propose a formal model for time point-based sequential data with operations that allow to construct sequences of events, organize them in an OLAP-like manner, and analyze them. To the best of our knowledge, this is the first formal model and query language for this class of data.